Economics 384: Research Project in Economics

ObjectiveThe Research Project in Economics is designed to be a capstone research experience for senior Economics majors. This senior-level research project is designed to fulfill these learning goals of researching, writing, and presenting a paper addressing a significant economic question or issue. Each student develops an economic question, which is then analyzed using an appropriate economic framework and evidentiary support. Students are asked to respond to criticisms to make this a wholesome research experience. In a nutshell, you will be "doing economics."!!!

Other upper-level Economics courses were offered to expose students to research opportunities to begin this process. Guided by the professor of record as well as the entire Economics department, students apply their knowledge from previous coursework as they "do economics". The small class size is purposefully kept small so that it permits greater interaction between the professor and each student, as well as more interaction among students.

Combining an Honors Thesis and ECON 384Students planning to write an Honors thesis should register for HONR 398 in the fall of their senior year.

Students are also expected to attend the class meetings of the ECON 384 course in the fall of their senior year. The ECON 384 models the research process in economics and provides useful deadlines for completing the research project. In addition, if circumstances prevent a student from completing an honors thesis, the student will have completed the work for ECON 384, a necessary requirement for graduating with an economics major.

The department chair will accept the substitution of HONR 398 for ECON 384 when auditing the student's application for degree.

Recent Work:Here are some recent abstracts from the ECON 384 projects:

Crime Rates, Income Inequality, and Density at the Neighborhood Level -

"An economic model of crime can help policy makers understand how income inequality and population density relate to crime on the Census Tract level. Higher levels of income inequality suggest more social tension and higher returns to crime while population density influences the probability of recognition and apprehension of criminals. My cross-sectional Poisson analysis of Los Angeles Census Tracts uses tract-level demographic data comes from the National Neighborhood Crime Study and PUMA-level income data from International Public Use MicroSample database. I find that income inequality, as measured by a Gini Coefficient, and population density both relate negatively and significantly with crime rates." Andrew Hovel (Fall 2013). Please check out the video:

An Empirical Analysis on Estimating the Demand for Housing Services:

"This research paper attempts to estimate the demand for housing services across the United States. More specifically, the research paper examines the price and income elasticity of demand and compare the results between a single market and multiple markets. An empirical analysis on 32 Metropolitan Statistical Areas in the year 2005 suggests that the price elasticity of demand for multiple markets is inelastic; and the price elasticity of demand has relatively smaller magnitude in multiple markets compared to corresponding elasticity in a single market. In addition, the income elasticity of demand has a relatively larger magnitude than the price elasticity of demand for multiple markets." By Nhu Nguyen (Fall 2013)Please check out the video:

Course Timeline:

Typically, the coursework involves these stages:

The research project and selecting a topic - Weeks 1-3

Initial written proposal and faculty review - Weeks 4-5

Expanded written proposal and preliminary bibliography - Weeks 5-6

Researching, research advice and first draft - Weeks 7-8

Small group discussions and practice oral presentations of work-in-progress - Week before the final presentation

Final/formal oral presentation

Final draft - At end of semester, after the final presentation.

Student Research:

Student: Bradley OlijnekResearch: Modeling Longshoremen's Earnings in the Containerized Era: An UpdateAbstract: This paper updates Talley’s (2002) research on longshoremen’s wages for the years 1973-1997. Using data for the period from 1998-2006 from the Integrated Public Use Microdata Series, the updated model estimates American longshoremen’s annual wage. This time period was chosen to follow Talley’s study and end before the Great Recession in the United States. During this period, increasing containerization continued to reduce the expense of moving cargo as increasing capital intensity helped to minimize the required amount of physical handling of goods. In other words, a large-scale substitution of capital for labor occurred in the cargo handling industry. At the same time, median wage in the longshoremen occupations fell over the period of study. By updating this earlier research, the empirical estimates more accurately measure the prevailing labor market conditions in this industry and reveals a declining geographic differential for longshoremen as well as a reduced influence of race and ethnicity in wage determination.

Student: Mary KormanResearch: Evaluating Differences in Number of Hours Worked per Week for People With and Without DisabilitiesAbstract: Even though the passing of the Americans with Disabilities Act of 1990 has opened many doors to the workforce for people with disabilities, there remain huge disparities in workforce patterns between people with disabilities and people without disabilities. This paper evaluates if variables that normally predict hours worked in the non-disabled population also have similar effects for disabled workers, and it further estimates the extent to which disability affects hours worked. An Ordinary Least Squares regression is performed to estimate the effect of work disability on the number of weekly hours worked. Results show that having a work disability has a negative and statistically significant effect on number of weekly hours worked. Results indicate that an individual with a work disability will spend 1.76 hours less per week at work, on average, than an individual without a work disability. Additionally, variables such wages and non-labor income have a similar effect on disabled workers’ participation as they do for non-disabled workers.

Student: Heather KaluzniakResearch: Health and Wealth: A Modified Solow Growth ModelAbstract: It is common to augment the Solow (1956) growth model by adding terms that represent additional components or influences of growth that are not otherwise captured by simple labor, capital, population, and depreciation variables. Given that a healthier and better educated population would intuitively be more productive, there is some reason to believe that greater health would augment the labor variable and have at least a short-run positive effect on economic growth. This research modifies the Solow model with a human capital variable to measure the level of health and education in a country. The attributes are measured by mortality rates and average years of schooling. The results of a cross-country analysis of 42 Sub-Saharan African countries demonstrate that improved health positively correlates with GDP (Gross Domestic Product) growth rates. In a further growth accounting exercise, it was revealed that human capital accounts for about a third of economic growth.

Student: Chad GuennigsmanResearch: Salary Determination in the NHLAbstract: This paper explores the causes and effects of wage discrimination among players in the National Hockey League. After exploring the various methods of estimating player salaries in the sports economics literature, the paper uses data from the 2016-2017 NHL season players to estimate wage functions for hockey players. This analysis extends prior analysis by also incorporating data on player statistics prior to contract signing, player free agency rights, and defensive player statistics. The results indicate that Unrestricted Free Agency has a positive and statistically significant effect on wages, and the paper also validates the intuition that compensation is based on important skill differences (i.e., forwards are paid according to the skills necessary for success as a forward and defensemen are paid based on skills need for success in that role).